Abstract: A system for a reliability of objects for a driver assistance or automated driving of a vehicle includes a plurality of sensors that include one or more sensor modalities for providing sensor data for the objects. An electronic tracking unit is configured to receive the sensor data to determine a detection probability (p_D) for each of the plurality of sensors for each of the objects, to determine an existence probability (p_ex) for each of the plurality of sensors for each of the objects, and to provide vectors for each of the objects based on the existence probability (p_ex) for each contributing one of the plurality of sensors for the specific object. The vectors are provided by the electronic tracking unit for display as an object interface on a display device. The vectors are independent from the sensor data from the plurality of sensors.

Abstract: Methods and systems for per-input port, per-control plane network data traffic class control plane policing in a network element are described. In one embodiment, the method comprises receiving control plane network data at an input port of a network element, wherein the control plane network data is data that is processed by the control plane. The method may also include classifying the control plane network data based on characteristics of the control plane network data. Furthermore, the method may include storing the control plane network data in one of a plurality of output queues for the input port based on a class of the control plane network data, and forwarding control plane network data from a selected one of the plurality of output queues to a control plane of the network element.

Abstract: For distributed processing using drift-based dynamic clustering of Internet of Things (IoT) devices, at a central device, a data source to be used for processing a workload is determined. A set is selected of devices operating within a threshold distance from the data source at a first time. A first subset of the set of devices is selected to form a cluster of devices. Each device in the first subset satisfies a clustering condition. A first device in the first subset is instructed to configure an application at the first device to participate in the cluster and process the workload. From a performance check on the first device, a change is discovered in a performance metric. In response to the change resulting from an increased demand for a computing resource at the first device, the first device is replaced with a second device from the first subset.

Abstract: Methods and systems for per-input port, per-control plane network data traffic class control plane policing in a network element are described. In one embodiment, the method comprises receiving control plane network data at an input port of a network element, wherein the control plane network data is data that is processed by the control plane. The method may also include classifying the control plane network data based on characteristics of the control plane network data. Furthermore, the method may include storing the control plane network data in one of a plurality of output queues for the input port based on a class of the control plane network data, and forwarding control plane network data from a selected one of the plurality of output queues to a control plane of the network element.

Abstract: The invention relates to the manufacture of foods, in particular to aerated confectionery products, like marshmallow-type products, to foam structuring compositions, and methods for preparing them. Provided is an aerated confectionery product having a density up to 0.5 g/cm3, the product comprising as foam structuring composition a combination of (i) a native potato protein; (ii) a gelling starch; and (iii) a highly branched starch (HBS) obtained by treatment of starch or a starch derivative with glycogen branching enzyme (EC 2.4.1.18), and wherein said HBS has a molecular branching degree of at least 6%, wherein the molecular branching degree is defined as the percentage of ?-1,6 glycosidic linkages of the total of ?-1,6 and ?-1,4 glycosidic linkages ((?-1,6/(?-1,6+?-1,4)*100%).

Abstract: The invention relates to confectionery products and methods for producing them. Provided is a chewy candy comprising a starch-based gelling agent, wherein said gelling agent is a highly branched starch (HBS), preferably wherein said HBS has a molecular branching degree of at least 6%, more preferably at least 6.5%. In a specific aspect, the chewy candy is essentially free of gelatin or other animal-derived ingredient.

Abstract: Systems and methods are describe herein for managing a transaction between two parties. A distributed ledger management service (DLMS) microservice receives an electronic document pertaining to a transaction from a user. The electronic document includes transactional data. A document type is determined by the DLMS microservice. A portion of the transactional data is extracted from the electronic document based on the document type. The portion of the transactional data is provided to a distributed ledger node for decentralized storage and further reporting to a third party.

Abstract: At a central device, a data source to be used for processing a workload is determined. A set is selected of devices operating within a threshold distance from the data source at a first time. A first subset of the set of devices is selected to form a cluster of devices. Each device in the first subset satisfies a clustering condition. A first device in the first subset is instructed to configure an application at the first device to participate in the cluster and process the workload. From a performance check on the first device, a change is discovered in a performance metric. In response to the change resulting from an increased demand for a computing resource at the first device, the first device is replaced with a second device from the first subset.

Abstract: For distributed processing using drift-based dynamic clustering of Internet of Things (IoT) devices, at a central device, a data source to be used for processing a workload is determined. A set is selected of devices operating within a threshold distance from the data source at a first time. A first subset of the set of devices is selected to form a cluster of devices. Each device in the first subset satisfies a clustering condition. A first device in the first subset is instructed to configure an application at the first device to participate in the cluster and process the workload. From a performance check on the first device, a change is discovered in a performance metric. In response to the change resulting from an increased demand for a computing resource at the first device, the first device is replaced with a second device from the first subset.

Abstract: For distributed processing using forecasted location-based IoT device clusters, at a central IoT device, a data source that is to be used and a duration for processing a workload is determined. A set of IoT devices operating within a threshold distance from the data source at a first time is selected. A subset of the set is selected to form a sub-cluster of IoT devices where a forecasted travel path of a member IoT device in the subset keeps the member within the threshold distance from the data source for the duration. A lightweight application is configured at a first IoT device in the subset which enables the first IoT device to participate in the sub-cluster and process the workload.

Abstract: Data packets are received at a communication device that is coupled to a network node in a communication network, to a gateway router that is coupled to other network nodes in the communication network, and to a further communication network. For each received data packet, a determination is made as to whether the received data packet is to be routed toward a destination by the communication device instead of by the gateway router. The received data packet is routed toward the destination by the communication device based on determining that the received data packet is to be routed toward the destination by the communication device instead of by the gateway router. Otherwise, the received data packet is switched from the communication device to the gateway router to be routed by the gateway router toward the destination.

Abstract: A multi-tool plier that includes a screwdriver bit that is integrally formed with a tip of the plier jaws. The multi-tool plier provides the user the mechanical advantages of applying a sufficient force to the bit and screw, improved torque, and on-axis operation of the handle to rotate the bit on the screw. Moreover, with the screwdriver bit conveniently located at the tip of the pliers, the screwdriver bit is always at the ready, allowing an uninterrupted transition between operations with the pliers and the screwdriver. The bit elements at the ends of the plier jaws cooperatively define a drive bit for a variety of rotary fastener, including a standard, a Phillips, a Torx, a square, an Allen, or other geometrically shaped drive bit.

Abstract: A method of managing an online support group to increase the odds that users will attain their wellness goals is disclosed. A request from a user to join a support group is received. A preference of the user with respect to a type of the support group is received. The support group is selected from a plurality of support groups based on the preference of the user and a preference of a member of the support group. Based on an acceptance by the user of an option to join the support group, the plurality of support groups is reorganized.

Abstract: For distributed processing using location-based IoT device clusters, using a processor and a memory at a central IoT device, a data source that is to be used for processing a workload is determined. A set of IoT devices that are operating within a threshold distance from the data source at a first time is selected. At the central IoT device, to form a cluster of IoT devices, a subset of the set of IoT devices is selected. Each IoT device in the subset satisfies a clustering condition. The processor at the central IoT device is instructed to configure a device application at a first IoT device in the subset of IoT devices, the device application enabling the first IoT device to participate in the cluster and process the workload.

Abstract: For distributed processing using forecasted location-based IoT device clusters, at a central IoT device, a data source that is to be used and a duration for processing a workload is determined. A set of IoT devices operating within a threshold distance from the data source at a first time is selected. A subset of the set is selected to form a sub-cluster of IoT devices where a forecasted travel path of a member IoT device in the subset keeps the member within the threshold distance from the data source for the duration. A lightweight application is configured at a first IoT device in the subset which enables the first IoT device to participate in the sub-cluster and process the workload.

Abstract: A method of managing an online support group to increase the odds that users will attain their wellness goals is disclosed. A request from a user to join a support group is received. A preference of the user with respect to a type of the support group is received. The support group is selected from a plurality of support groups based on the preference of the user and a preference of a member of the support group. Based on an acceptance by the user of an option to join the support group, the plurality of support groups is reorganized.

Abstract: For distributed processing using clustering of interdependent Internet of Things (IoT) devices, at a central device, a data source to be used for processing a workload is determined. A set is selected of devices operating within a threshold distance from the data source at a first time. A first subset of the set of devices is selected. Each device in the first subset satisfies a clustering condition. A first device in the subset is instructed to configure a lightweight application to participate in the cluster and process the workload. The processing of the workload is halted on a second device, where the first device has a processing dependency on the second device in processing the workload. A preserved current state of processing the workload is transferred from the first device to a third device. The processing of the workload is continued using the second device and the third device.

Abstract: Systems, methods, and non-transitory computer readable media can obtain a plurality of change points that are each indicative of a potential change in a curve relating to a metric associated with a system. A prediction model for providing forecasts relating to the metric can be generated. A seasonality model for predicting seasonality associated with the metric can be generated. A combined forecast model can be generated based on the prediction model and the seasonality model.

Abstract: For distributed processing using forecasted location-based IoT device clusters, at a central IoT device, a data source that is to be used and a duration for processing a workload is determined. A set of IoT devices operating within a threshold distance from the data source at a first time is selected. A first subset of the IoT devices is selected to form a cluster of IoT devices where each IoT device satisfies a clustering condition. A second subset of the first subset is selected to form a sub-cluster of IoT devices where a forecasted travel path of a member IoT device in the second subset keeps the member within the threshold distance from the data source for the duration. A lightweight application is configured at a first IoT device in the second subset which enables the first IoT device to participate in the sub-cluster and process the workload.

Abstract: For distributed processing using sampled clusters of location-based Internet of Things (IoT) devices, at a central device, a data source to be used for processing a workload is determined. A set is selected of devices operating within a threshold distance from the data source at a first time. A first subset including a first sample number of devices is selected from the set. A ratio is determined of a first amount of a computing resource needed to process the workload and a second amount of the computing resource available in the first subset to process the workload. From the set, to form a cluster, a second subset is selected of a size at least equal to a multiple of the ratio and the first sample number. Each device in the second subset satisfies a clustering condition. A lightweight application is configured at the first device to process the workload.